273 citations · 988 across the 24 of their papers we have counts for
4 papers · 1 filter
Tomographic Auto-Encoder: Unsupervised Bayesian Recovery of Corrupted Data
Francesco Tonolini, Pablo G. Moreno, Andreas Damianou +1
We propose a new probabilistic method for unsupervised recovery of corrupted data. Given a large ensemble of degraded samples, our method recovers accurate posteriors of clean valu…
Empirical Bayes Transductive Meta-Learning with Synthetic Gradients
Shell Xu Hu, Pablo G. Moreno, Yang Xiao +4
We propose a meta-learning approach that learns from multiple tasks in a transductive setting, by leveraging the unlabeled query set in addition to the support set to generate a mo…
Online Constrained Model-based Reinforcement Learning
Benjamin van Niekerk, Andreas Damianou, Benjamin Rosman
Applying reinforcement learning to robotic systems poses a number of challenging problems. A key requirement is the ability to handle continuous state and action spaces while remai…
Similarity of Neural Networks with Gradients
Shuai Tang, Wesley J. Maddox, Charlie Dickens +2
A suitable similarity index for comparing learnt neural networks plays an important role in understanding the behaviour of the highly-nonlinear functions, and can provide insights…